Economically Optimum Design of a Synthetic  Chart

Yeong, Wai Chung; Khoo, Michael B. C.; Wu, Zhang; Castagliola, Philippe

doi:10.1002/qre.1264

Cited by 31 publications

(29 citation statements)

References 47 publications

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“…Yeong et al proposed the first economic model for the S1 chart in which they formulated an algorithm to find the optimal values of the chart's design parameters, which minimize the net sum of all costs involved, so that the chart can be operated at an economically optimal level by using the approximation of the cost function in Chung . Recently, Yeong et al further showed the economic efficiency of the S1

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chart as compared with that of the ordinary

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chart.…”

Section: Literature Reviewmentioning

confidence: 99%

An overview of synthetic‐type control charts: Techniques and methodology

Rakitzis

Chakraborti

Shongwe

et al. 2019

Quality & Reliability Eng

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In this paper, we provide an overview of a class of control charts called the synthetic charts. Synthetic charts are a combination of a traditional chart (such as a Shewhart, CUSUM, or EWMA chart) and a conforming run‐length (CRL) chart. These charts have been considered in order to maintain the simplicity and improve the performance of small and medium‐sized shift detection of the traditional Shewhart charts. We distinguish between different types of synthetic‐type charts currently available in the literature and highlight how each is designed and implemented in practice. More than 100 publications on univariate and multivariate synthetic‐type charts are reviewed here. We end with some concluding remarks and a list of some future research ideas.

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chart as compared with that of the ordinary

\overset{X}{true}

chart.…”

Section: Literature Reviewmentioning

confidence: 99%

An overview of synthetic‐type control charts: Techniques and methodology

Rakitzis

Chakraborti

Shongwe

et al. 2019

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…They used various tools which can maximize their individual benefits from a holistic point of view of total quality. Yeong et al [20] proposed an economic model for the synthetic chart that is an integration of the X chart and the CRL chart. Numerical examples, based on different values of input parameters were given, and sensitivity analyses of the parameters were performed.…”

Section: -P2mentioning

confidence: 99%

Cost comparisons of modifiedX̅chart for autocorrelated observations

Prajapati

2016

Int. J. Metrol. Qual. Eng.

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Abstract. This paper presents the economic design of modified X chart for autocorrelated data and comparison with the economic design of Shewhart's X chart. An attempt has been made to counter autocorrelation by designing the modified X chart; as the cost of operating a process control system is an important element in the economic design of control charts. The economic designs of both modified and Shewhart X charts for autocorrelated observations are presented; using Lorenzen-Vance [1] cost model. The modified X chart is based upon sum of chi-squares and has simplicity like Shewhart X chart but more efficient than standard chart. Two sets of parameters suggested by Montgomery [2] are used to determine the optimal sampling intervals (h) and expected costs per hour. It shows that sampling interval (h) and expected cost/hour (C) depend upon various parameters of chart, used in this model. The expected costs/hour (C) for both the charts are computed for sample sizes of 2 and 4 at the various levels of correlation and process shifts in mean. It is concluded that at each level of correlation and shift in the process mean, the expected costs/hour of the modified X chart are lower than the Shewhart chart.

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“…The notion of selecting chart parameters to minimise cost over time has intuitive appeal, especially when the economic consequences of the design are significant. Therefore, the research community (see Xie, Tang, and Goh 2001;Zhang, Xie, and Goh 2005;Yeong et al 2012;Park 2013) has allocated part of its efforts to the development and improvement of optimisation models for economic design of control charts.…”

Section: Introductionmentioning

confidence: 99%

Economic modelling for statistical process control subject to a general quality deterioration

Li¹,

Xie

2015

International Journal of Production Research

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The applications of control chart have traditionally focused on the detection of step shifts in process mean. However, changes are usually gradual, not as perfect step shifts. The common consideration of a shift as a step function does not always adequately describe what actually happens in practice. Hence, there is a need for more realistic assumptions to be incorporated. This paper employs a Markov chain approach and provides a way to quantitatively measure the economic performance of control charts in the presence of a more general quality deterioration mechanism. The finite production run is considered in the model as it has become a very important production mode at present and the process failure mechanism is described by geometric distribution. The chart properties, particularly on the issues of the quality deterioration mechanism, are investigated. The findings provide critical insights on the use of step shift assumption when designing control charts.

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Economically Optimum Design of a Synthetic Chart

Cited by 31 publications

References 47 publications

An overview of synthetic‐type control charts: Techniques and methodology

An overview of synthetic‐type control charts: Techniques and methodology

Cost comparisons of modifiedX̅chart for autocorrelated observations

Economic modelling for statistical process control subject to a general quality deterioration

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